Admiral Adama has entered the chat.
6,180 karma · joined October 24, 2017
A standard western personality trait I’ve been confronted with repeatedly over the last… hmm. Well that got depressing real quick.
"Nonappropriated fund activities" are a thing though?
As an aside, your username reminds me it’s about time for another rewatch of cowboy bebop
They might simply be tired of listening to armchair protestors who don’t take even the most basic actions to backup their words.
There are basic ways to act, not just talk, to support resistance to this path. And people, even some people reading this very comment, are unwilling to take those basic actions while also whining loudly and/or downvoting in angst.
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I forgot glass was even a thing as I immediately turned it on day one.
Had the filtering been done during the initial document storage, then the cost would have been much cheaper than your $2,000 estimate. Essentially binning the receipts based on "eggs" or "no eggs" would be free. But, crucially, what happens when the question changes from price per egg to price per gallon of milk? Now the whole stack would need to be sorted again. The $2,000 manual classification would need to be re-applied.
Isn't traditional ML-based classification cheaper for this problem at industrial scale than an LLM though? The OP did of course attempt more traditional generic off-the-shelf OCR tools, but let's consider proper bespoke industrial ML.
Just as a off-the-cuff example, I would probably start with building a tool that locates the date/time from a receipt and takes an image snip of it. Running ONLY image snips through traditional OCR is more successful than trying to extract text from an entire receipt. I would then train a separate tool that extracts images of line items from a receipt that includes item name and price. Yet another tool could then be trained to classify items based on the names of the items purchased, and a final tool to get the price. Now you have price, item, and date to put into your database.
Perhaps generating the training data to train the item classifier is the only place I could see an LLM being more cost effective than a human, but classifying tiny image snips is not the same as one-shotting an entire receipt. As an aside, if there's any desire to discuss how expensive training ML is, don't forget the price to train an LLM as well.
All of this is to say I believe traditional ML is the solution. I'm still not seeing the value prop of LLMs at the industrialization scale outside of very targeted training data generation. A more flippant conclusion might be that we can replace a lot of the parts of data science that makes PhD types get bored with creating traditional ML solutions.
Spherical cows aside though, I do agree with you that I should not consider scalability as a given.
You could pay a human to read receipts, 1 every 30 seconds (that’s slow!), $15/hr (twice the US federal minimum wage!), plus tax and overhead ($15x1.35) comes out to $20.25/hr over 5 hours. $101 all in.
Sure, sure, a human solution doesn’t scale. But this sort of project makes me feel like we haven’t hit the industrialization moment that i thought we had quite yet.
Feels analogous to looking for cold fusion because of the downsides of fission.
I didn't get a significant sense of loss from this article though. Especially given the downsides of PFAS.
Sometimes it's a lack of capacity for novel thinking. Sometimes it's fear caused by past trauma. Or it can be age. Or an inability to overcome habits. The list goes on, but the point is that I've had to work with or supervise employees (even in IT!) that didn't have a creative bone in their body. It wasn't a lack of motivation, it was usually something on the list above.
These people absolutely deserved the feeling of being useful, and those are the people I'm most concerned for in this new post-LLM world. The creative types will most likely be fine, but we have words to describe creativity as an acknowledgement that there can be an absence of creativity.
Given the UK's typical solar exposure[0], and the quality of panels you can pickup at a supermarket, this has gotta be a net negative for a family right?
Probably zero grandmothers outside the west, and very few grandmothers within the west, know what NFT even stands for.